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Energy Consumption Modeling of Stereolithography‐Based Additive Manufacturing Toward Environmental Sustainability
Author(s) -
Yang Yiran,
Li Lin,
Pan Yayue,
Sun Zeyi
Publication year - 2017
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12589
Subject(s) - energy consumption , stereolithography , computer science , sustainability , consumption (sociology) , quality (philosophy) , product (mathematics) , remanufacturing , process engineering , production (economics) , industrial ecology , energy accounting , industrial engineering , manufacturing engineering , environmental economics , mechanical engineering , engineering , mathematics , economics , ecology , social science , sociology , electrical engineering , biology , philosophy , geometry , macroeconomics , epistemology
Summary Additive manufacturing (AM), also referred as three‐dimensional printing or rapid prototyping, has been implemented in various areas as one of the most promising new manufacturing technologies in the past three decades. In addition to the growing public interest in developing AM into a potential mainstream manufacturing approach, increasing concerns on environmental sustainability, especially on energy consumption, have been presented. To date, research efforts have been dedicated to quantitatively measuring and analyzing the energy consumption of AM processes. Such efforts only covered partial types of AM processes and explored inadequate factors that might influence the energy consumption. In addition, energy consumption modeling for AM processes has not been comprehensively studied. To fill the research gap, this article presents a mathematical model for the energy consumption of stereolithography (SLA)‐based processes. To validate the mathematical model, experiments are conducted to measure the real energy consumption from an SLA‐based AM machine. The design of experiments method is adopted to examine the impacts of different parameters and their potential interactions on the overall energy consumption. For the purpose of minimization of the total energy consumption, a response optimization method is used to identify the optimal combination of parameters. The surface quality of the product built using a set of optimal parameters is obtained and compared with parts built with different parameter combinations. The comparison results show that the overall energy consumption from SLA‐based AM processes can be significantly reduced through optimal parameter setting, without observable product quality decay.